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Collaborative Filtering for Rails
License: MIT License
This project forked from maccman/acts_as_recommendable
Collaborative Filtering for Rails
License: MIT License
ActsAsRecommendable =================== ActsAsRecommendable is a plugin for Rails that simplifies collaborative filtering The plugin provides a mechanism for finding loose associations between users and items which we can tell you * Given a user, return other similar users based on what items they have all bought/bookmarked/rated/etc * Given a user, return recommended items based on the items bought/bookmarked/rated/etc by that user and the items bought/bookmarked/rated/etc by other users. The plugin calculations can be made online and offline and stored using the rails cache (such as memcache) for online retrieval. Online retrieval of recommendations uses item-based collaborative filtering using the offline items similarity matrix stored in the cache. This can give up-to-date results with a much lower processing overhead. Much thanks to Toby Segaran and his excellent book Programming Collective Intelligence (http://oreilly.com/catalog/9780596529321/). Features ======== Use join rating scores Using abitary calculated scores Similar Items Recommended Users Cached dataset Current Release =============== v0.1 should be considered early alpha and not ready for production applications. Lots of performance optimisations still to be done. Example ======= class Book < ActiveRecord::Base has_many :user_books has_many :users, :through => :user_books end class UserBook < ActiveRecord::Base belongs_to :book belongs_to :user end class User < ActiveRecord::Base has_many :user_books has_many :books, :through => :user_books acts_as_recommendable :books, :through => :user_books end user = User.find(:first) user.similar_users #=> [...] user.recommended_books #=> [...] book = Book.find(:first) book.similar_books #=> [...] Example 2 ========= class Movie < ActiveRecord::Base has_many :user_movies has_many :users, :through => :user_movies end class UserMovie < ActiveRecord::Base belongs_to :movie belongs_to :user end class User < ActiveRecord::Base has_many :user_movies has_many :movies, :through => :user_movies acts_as_recommendable :movies, :through => :user_movies, :score => :score # 'score' is an attribute on the users_movies table end user = User.find(:first) user.similar_users #=> [...] user.recommended_movies #=> [...] Example 3 ========= class Book < ActiveRecord::Base has_many :user_books has_many :users, :through => :user_books, :use_dataset => true # Uses cached dataset end class UserBook < ActiveRecord::Base belongs_to :book belongs_to :user end class User < ActiveRecord::Base has_many :user_books has_many :books, :through => :user_books acts_as_recommendable :books, :through => :user_books end user = User.find(:first) user.recommended_books #=> [...] # The example above uses a cached dataset. # You need to generate a cached dataset every so often (depending on how much your content changes) # You can do that by calling the rake task recommendations:build, you should run this with a cron job every so often. # If you only want to use the dataset in production put this in production.rb: User.aar_options[:use_dataset] = true # Note: # user.similar_users doesn't use the dataset # # The advantage of using a dataset is that you don't need to load all the users & items into # memory (which you do normally). The disadvantage is that you won't get as accurate results. # Contact ======= [email protected] Copyright (c) 2008 Made by Many Ltd, released under the MIT license
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